Hunyuan Multimodal Algorithm Researcher Intern(Omni-Modal)

Shine BrightX LLC; Palo Alto (CA); In loco; USD 80.000 - 125.000; Tempo pieno

Vantaggi offerti da questo lavoro

Paid sick leave

Paid holidays

Company-sponsored medical plan

Descrizione del lavoro

Shine BrightX LLC in Palo Alto, CA is seeking a researcher to advance Omni multimodal large models. You will design training data, develop foundational models, and optimize pre-training, SFT and RL while evaluating capabilities and exploring downstream applications.

You will analyze R&D challenges, identify bottlenecks from first principles, and push leading-edge performance. The role invites research into next‑generation architectures for cross‑modal understanding and generation, with emphasis

Competenze

• Bachelor’s degree required; higher degrees preferred.
• Experience with large-scale multimodal data processing.
• Strong foundation in deep learning; diffusion/autoregressive models a plus.
• Publications or cross-modal research experience preferred.
• Experience with distributed training and inference optimization.

Mansioni

• Conduct research and development of Omni multimodal large models, including training data design, foundational model algorithm design, optimization of pre-training/SFT/RL, model capability evaluation, and exploration of downstream applications.
• Analyze R&D challenges scientifically, identify performance bottlenecks, and develop solutions based on first principles to accelerate model development and maintain leading-edge performance.
• Explore diverse paradigms for Omni-modal understanding and generation, research next-generation model architectures, and advance multimodal model capabilities.

Conoscenze

Multimodal DL

Data processing

Model development

Distributed training

Diffusion models

ACM/NOI experience

Formazione

Bachelor’s degree or higher in CS/AI/math

Strumenti

PyTorch

GPU/CUDA

Descrizione del lavoro

Your Role

Key responsibilities include:

• Conduct research and development of Omni multimodal large models, including training data design, foundational model algorithm design, optimization of pre-training/SFT/RL, model capability evaluation, and exploration of downstream applications.
• Analyze R&D challenges scientifically, identify performance bottlenecks, and develop solutions based on first principles to accelerate model development and maintain competitive, leading-edge performance.
• Explore diverse paradigms for Omni-modal understanding and generation, research next-generation model architectures, and advance multimodal model capabilities.

About You

The company is looking for:

• Bachelor’s degree (full-time preferred) or higher in Computer Science, Artificial Intelligence, Mathematics, or related fields; graduate degrees prioritized.
• Hands-on experience in large-scale multimodal data processing and high-quality data generation preferred.
• Strong foundation in deep learning algorithms and practical experience in large model development; familiarity with Diffusion Models and Autoregressive Models is advantageous.
• Publication in top-tier conferences or experience in cross-modal research (e.g., audio-visual) preferred.
• Proficiency in deep learning network implementation, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization; practical experience is a plus.
• Participation in ACM or NOI competitions is highly valued.
• Strong learning agility, communication skills, teamwork, and curiosity.

Compensation & Benefits

• Base pay range: $80,168.40 to $124,800.00 per year, varying by knowledge, skills, and experience.
• Eligibility for 1 hour of paid sick leave for every 30 hours worked.
• Up to 13 paid holidays annually.
• Full-time interns eligible to enroll in the Company-sponsored medical plan, subject to plan terms.